AI in Surgical Planning: What Brainlab Elements Already Does

Artificial intelligence in surgery is often described as something coming soon. Inside the planning software many hospitals already own, it is not coming. It is running today. Brainlab Elements is a clear example, and it is the planning layer Brainz brings to neurosurgery and spine teams across the UAE and GCC.

The wider clinical literature makes the direction plain. Recent reviews of machine learning in spine and cranial surgery describe deep learning models that reconstruct patient anatomy in seconds rather than hours, and that propose screw trajectories with reported entry-point errors of a few millimeters. The value is not novelty. It is time returned to the surgeon and consistency added to the plan.

What "AI in planning" actually means

In a planning suite, AI does the repetitive, high-effort work that used to sit between a scan arriving and a surgeon being ready to operate. It fuses image sets, outlines structures, segments anatomy and suggests approaches. The surgeon still reviews, edits and decides. The software removes the manual labor, not the clinical judgment.

Brainlab describes Elements exactly this way: interactive and semi-automated modules that turn any scan into a 3D surgical plan through image fusion, distortion correction, segmentation, target outlining, fiber tracking and trajectory planning. The plan then flows straight into navigation in theatre.

Segmentation: from hours of contouring to a proposal in seconds

Segmentation is where the time savings are most visible. Elements Segmentation Cranial performs fully automated, knowledge-based segmentation of relevant brain structures, replacing a slow manual contouring step. Elements SmartBrush adds semi-automatic tumor outlining, and Brainlab notes its machine learning technology can help speed up planning and reduce variation between reviewers.

The newer Elements AI Tumor Segmentation goes a step further. It returns a semi-automatic segmentation proposal for diagnosed cranial tumors, including metastases, meningiomas and gliomas, from contrast-enhanced T1-weighted MRI, built on a U-net architecture trained on registry-based annotated datasets. This feature is not yet commercially available in every country, so scope depends on local regulatory status.

From tumor outlining to trajectory planning

A plan is more than an outline. Elements Trajectory Planning lets the surgeon position target and entry points with all relevant data in one place: the target structure, segmented objects and tracked fiber pathways. Fiber tracking itself, through Elements Fibertracking, brings research-grade tractography into routine practice to help protect eloquent white matter during resection. Together these steps let the team rehearse the approach before the first incision, then carry that same plan into the navigation field.

Spine planning joins the suite

The clearest sign of where this is going arrived in May 2026, when Brainlab received the CE mark and EU market launch for Elements Spine Planning. The AI-based software analyzes patient-specific spinopelvic parameters and helps plan sagittal alignment, a key factor in deformity and complex spinal cases. It builds a patient-specific avatar to visualize correction scenarios, and it is implant-agnostic, so it fits whatever system a hospital uses.

Brainlab positions the tool as a complement to the surgeon, not a replacement: a structured way to define preoperative targets and carry them into intraoperative execution. That framing matters for procurement teams weighing AI claims. The useful question is not whether software is intelligent, but whether it makes planning faster, more consistent and easier to hand to the operating room.

What Brainz adds

Software is only as good as its integration. Brainz handles deployment, data and image connectivity, and surgeon onboarding, and ties Elements planning to the wider neurosurgery and spine surgery technology programs a hospital is building. AI in planning is the least disruptive place to start, because it changes the work before the operating room, not inside it. A demonstration on your own cases is the fastest way to judge it.